ALBUQUERQUE, NM — A new study led by researchers at the national Centers for Disease Control and Prevention is drawing renewed attention to a long-standing issue that has quietly distorted public health statistics for decades: the racial misclassification of American Indian and Alaska Native (AI/AN) individuals on death certificates.
Racial misclassification occurs when a person’s race is recorded incorrectly on official records, such as death certificates. For AI/AN individuals, this often means being classified as white, Hispanic or another racial group, leading to inaccurate mortality statistics.
Misclassification can happen for several reasons: unfamiliarity with tribal identities, assumptions made by those completing paperwork, or limitations in data systems that don’t reflect the diversity and complexity of AI/AN identities.
But the problem isn’t just a bureaucratic oversight. It’s a barrier to understanding—and ultimately addressing—the significant health disparities that affect AI/AN communities, according to the authors of a recent study.
“Non-Hispanic American Indian and Alaska Native people experience more deaths from all causes, including chronic diseases like cancer, compared to Non-Hispanic White people,” explained Stephanie C. Melkonian, PhD, an epidemiologist at CDC’s Division for Cancer Prevention and Control. “But because of racial misclassification on death certificates, these disparities have been underestimated for a long time.”
The study, published in the American Journal of Epidemiology, focused on improving the accuracy of AI/AN mortality data using a technique known as data linkage. By connecting death records from the National Death Index (NDI) with patient registration data from the Indian Health Service (IHS), the research team was able to correct racial misclassifications and identify deaths that had previously been misattributed to other racial groups.1
The results were striking. Of the population studied, 2,998 individuals—12%—had been incorrectly classified on their death certificates. Once corrected, the data revealed that death rates among AI/AN individuals were significantly higher than previously reported. The disparities between AI/AN and Non-Hispanic White populations were also more pronounced than earlier estimates suggested.
Geographic differences stood out. “We were surprised by how much variation there was across different regions,” Melkonian noted. “Some of the highest racial misclassification occurred in the Southern Plains and Pacific Coast areas.”
The linkage method, long used in cancer surveillance, proved to be a powerful tool for correcting mortality data. “Every year, central cancer registries funded by CDC’s National Program of Cancer Registries link cancer incidence data with the Indian Health Service (IHS) patient registration database to get the most accurate estimates possible of how many American Indian and Alaska Native individuals were diagnosed with cancer,” Melkonian explained. “For this study, we did a similar linkage with data from the IHS patient database and data from the National Death Index (NDI) to get the most accurate estimates of mortality data for AI/AN individuals. This data will be included in our USCS AI/AN Mortality Database.”
Accurate mortality data isn’t just a matter of statistical precision—it’s foundational to public health planning. “When data for a group like the AI/AN population is inaccurate, we can’t fully understand what’s driving higher death rates in those communities,” Melkonian told U.S, Medicine. “That, in turn, limits our ability to respond.”
In practical terms, this could mean the difference between having—or not having—culturally appropriate cancer screening programs, chronic disease management resources, or targeted mental health services in AI/AN communities.
“When AI/AN individuals are misclassified, it creates a false narrative that fewer people from these communities are dying of certain causes,” Melkonian said. “This results in an underestimation of the true burden of disease and hinders our ability to identify and address health disparities.”
In the case of cancer, for instance, the improved mortality data will allow the CDC to better study survival rates among AI/AN populations. “This study looked at all causes of death, including cancer. Having accurate cancer death data will help CDC study cancer survival in AI/AN populations in the future,” she added.
While the study marks a major advancement, the researchers acknowledge that it isn’t a complete solution.
Because IHS only serves members of federally recognized tribes, the corrected data still doesn’t include all AI/AN individuals. “We know that we are not correcting race misclassification for everyone in the country,” Melkonian said, “but our estimates are better than what has been published previously.”
Still, the findings highlight an important path forward. Future work could expand linkage efforts to additional datasets, partner with tribes and urban AI/AN organizations, and improve the training of those who complete death certificates.
“Accurate mortality data is essential for understanding the health challenges faced by different populations,” Melkonian emphasized. “Without reliable race/ethnicity data, it’s difficult to design and implement effective public health programs aimed at improving outcomes in AI/AN communities.”
The researchers suggested that their study demonstrates the power of collaboration between federal agencies like the CDC, Indian Health Service, and National Center for Health Statistics to not only uncover hidden disparities—but to begin correcting them.
- Jim MA, Arias E, Haverkamp DS, Paisano R, Apostolou A, Melkonian SC. Improving Quality of Mortality Estimates Among Non-Hispanic American Indian and Alaska Native People, 2020. Am J Epidemiol. Published online May 2, 2025. doi:10.1093/aje/kwaf094
